移动测量技术及其应用

讨论了全球导航卫星系统（global navigation satellite system，GNSS）/里程计（odometer，ODO）/惯性导航系统（inertial navigation system，INS）组合定位定姿中误差校正与ODO/INS组合导航两个方面的问题。针对里程计刻度因子和安装误差角的校正，在不改变原GNSS/INS滤波器的基础上，设计了GNSS/INS与INS/ODO两级卡尔曼滤波器级联结构，将INS导航误差与里程计刻度因子误差、安装误差角分别列入两个滤波器的系统状态中，在GNSS连续观测和固定模糊度条件下，利用里程计和惯导里程增量之差作为INS/ODO卡尔曼滤波器的外部观测，对误差进行校正。
另一方面，使用校正过的里程计和安装误差角，在GNSS失锁条件下对INS进行观测和修正。跑车实验结果表明，本文算法可以有效校正里程计刻度因子和定位定姿（positioning and orientaton system，POS）安装误差角，同时大幅提高GNSS失锁条件下的定位精度，配合平滑卡尔曼滤波器，可将城市移动测量两分钟GNSS失锁条件下的定位误差控制在0.5 m以内。

Mobile Mapping Technology and Its Applications

In urban mobile mapping activity, odometer data is used to complement global navigation satellite system (GNSS)/ inertial navigation system (INS) data in positioning & orientation systems (POSs). We analyze the two error sources in POS, misalignment and odometer scale factor error, and their propagation in ECEF. A cascaded extend Kalman filter (EKF) was designed to estimate errors without changing the GNSS/INS EKF, after which is the INS/Odometer (ODO) EKF. Navigation errors and misalignment, and scale factor error are modeled as system states in two EKFs, respectively. Given GNSS continuous observation and fixed ambiguity, the INS was effectively calibrated by GNSS/INS EKF and its position increment was used as the measurement of the INS/ODO EKF.
Meanwhile, the calibrated odometer was used as an observation for INS when the GNSS experienced loss of lock. These tests indicate that the algorithm can calibrate misaligned angles of the POS and the scale factor of the odometer. Consequently, positioning accuracy was significantly improved when GNSS experienced loss of lock. Accuracy could be restricted in half a meter when two minutes GNSS gap happened in the process of mobile mapping with the use of a smoothing Kalman filter.